time series for nutrient data

I need help plotting a time series for the Nitrate+Nitrite and then a second for Phosphate but I'm unsure on how to go about it.

The day/month of collection is also on there.

I need to see if wind stress has an impact on how nutrinets move through the water column so plotting a series over the days in June would be ideal.

I'm not to sure if I'd need to take an average of each Nutrient collection for one CTD cast or?

Answer 1

[Star Strider]

Try this:

T1 = readtable('emily bristow D352_CTD_NUTRIENTS.xlsx',  'VariableNamingRule','preserve'); 
T2 = T1(:,16);
DayLabels = T2{~ismissing(T2),:};
UniqueDayLabels = unique(DayLabels);
T2 = fillmissing(T2, 'previous', 'DataVariables',{('Data Collected')});
T1.('Data Collected') = T2;
DayGrps = findgroups(T1.('Data Collected'));
MeanNO2NO3 = splitapply(@nanmean,T1.('Nitrate + Nitrite (μM)'),DayGrps);
NutrientByDate = table(UniqueDayLabels, MeanNO2NO3, 'VariableNames',{'Data Collected','Mean Nitrate + Nitrite (μM)'})

DayNr = regexp(NutrientByDate{:,1},'\d*','match');
[~,NutrientByDateSortedIdx] = sort(str2double([DayNr{:}]));
NuO2NO3ByDateSorted = NutrientByDate(NutrientByDateSortedIdx,:)

producing:

NutrientByDate =

  15×2 table

    Data Collected    Mean Nitrate + Nitrite (μM)
    ______________    ___________________________

    {'10th June'}                6.4595          
    {'11th June'}                5.0186          
    {'12th June'}                6.1182          
    {'13th June'}                4.7663          
    {'16th June'}                4.2824          
    {'17th June'}                 4.079          
    {'19th June'}                 3.945          
    {'20th June'}                6.9626          
    {'3rd June' }               0.20307          
    {'4th June' }                4.2168          
    {'5th June' }                5.9074          
    {'6th June' }                6.3682          
    {'7th June' }                6.0618          
    {'8th June' }                6.3556          
    {'9th June' }                5.4644   

Sorting them takes a bit more effort:

DayNr = regexp(NutrientByDate{:,1},'\d*','match');
[~,NutrientByDateSortedIdx] = sort(str2double([DayNr{:}]));
NutrientByDateSorted = NutrientByDate(NutrientByDateSortedIdx,:)

producing:

NutrientByDateSorted =

  15×2 table

    Data Collected    Mean Nitrate + Nitrite (μM)
    ______________    ___________________________

    {'3rd June' }               0.20307          
    {'4th June' }                4.2168          
    {'5th June' }                5.9074          
    {'6th June' }                6.3682          
    {'7th June' }                6.0618          
    {'8th June' }                6.3556          
    {'9th June' }                5.4644          
    {'10th June'}                6.4595          
    {'11th June'}                5.0186          
    {'12th June'}                6.1182          
    {'13th June'}                4.7663          
    {'16th June'}                4.2824          
    {'17th June'}                 4.079          
    {'19th June'}                 3.945          
    {'20th June'}                6.9626   

Doing Phosphate separately:

T2 = T1(:,16);
DayLabels = T2{~ismissing(T2),:};
UniqueDayLabels = unique(DayLabels);
T2 = fillmissing(T2, 'previous', 'DataVariables',{('Data Collected')});
T1.('Data Collected') = T2;
DayGrps = findgroups(T1.('Data Collected'));
MeanPO4 = splitapply(@nanmean,T1.('phosphate  (μM)'),DayGrps);
PhosphateByDate = table(UniqueDayLabels, MeanPO4, 'VariableNames',{'Data Collected','Mean phosphate  (μM)'})

DayNr = regexp(PhosphateByDate{:,1},'\d*','match');
[DayNrSorted,PhospahteByDateSortedIdx] = sort(str2double([DayNr{:}]));
PhosphateByDateSorted = PhosphateByDate(PhospahteByDateSortedIdx,:)

produces:

NutrientByDateSorted =

  15×2 table

    Data Collected    Mean phosphate  (μM)
    ______________    ____________________

    {'3rd June' }           0.10776       
    {'4th June' }           0.36712       
    {'5th June' }               NaN       
    {'6th June' }            0.4977       
    {'7th June' }           0.50817       
    {'8th June' }           0.48635       
    {'9th June' }            0.4276       
    {'10th June'}           0.44522       
    {'11th June'}           0.36299       
    {'12th June'}           0.42828       
    {'13th June'}           0.35977       
    {'16th June'}           0.35638       
    {'17th June'}            0.3191       
    {'19th June'}            0.2708       
    {'20th June'}           0.45897    

And putting it all together:

DateVar = compose('%2d June', DayNrSorted);
NO2No3PO4 = table(datetime(DateVar(:), 'InputFormat','dd MMMM', 'Format','dd MMMM'), NuO2NO3ByDateSorted{:,2}, PhosphateByDateSorted{:,2}, 'VariableNames',{'Data Collected','Nitrate + Nitrite (μM)','Mean phosphate  (μM)'})
VarNames = NO2No3PO4.Properties.VariableNames;

figure
plot(NO2No3PO4{:,1}, NO2No3PO4{:,2:3})
xlabel(VarNames{1})
ylabel('Concentration')
legend(VarNames{[2 3]}, 'Location','E')
grid
set(gca, 'XTickLabelRotation',60)

with the plot:

This is definitely not a trivial problem!

EDIT — (5 Dec 2020 at 20:08)

Added consolidated table ‘NO2No3PO4’ and plot figure.

.

[emily bristow]

That's perfect, thank you so much!

[Star Strider]

As always, my pleasure!